Evolving national park models: The emergence of an economic imperative and its effect on the contested nature of the 'national' park concept in Northern Ireland.

National park models have evolved in tandem with the emergence of a multifunctional countryside. Sustainable development has been added to the traditional twin aims of conservation and recreation. This is typified by recent national park designations, such as the Cairngorms National Park in Scotland. A proposed Mournes national park in Northern Ireland has evolved a stage further with a model of national park to deliver national economic goals envisaged by government. This seeks to commodify the natural landscape. This paper compares Cairngorm and Mourne stakeholders’ views on the principal features of both models: park aims, management structures and planning functions. While Cairngorm stakeholders were largely positive from the outset, the model of national park introduced is not without criticism. Conversely, Mourne stakeholders have adopted an anti-national park stance. Nevertheless, the model of national park proposed possessing a strong economic imperative, an absence of the Sandford Principle as a means to manage likely conflicts, and lacking any planning powers in its own right, may still be insufficient to bring about widespread support for a Mourne national park. Such a model is also likely to accelerate the degradation of the Mourne landscape. Competing national identities (British and Irish) provide an additional dimension to the national park debate in Northern Ireland. Deep ideological cleavages are capable of derailing the introduction of a national park irrespective of the model proposed. In Northern Ireland the national park debate is not only about reconciling environmental and economic interests but also political and ethno-national differences.

Rapidly Evolving and Luminous Transients from Pan-STARRS1

In the past decade, several rapidly evolving transients have been discovered whose timescales and luminosities are not easily explained by traditional supernovae (SNe) models. The sample size of these objects has remained small due, at least in part, to the challenges of detecting short timescale transients with traditional survey cadences. Here we present the results from a search within the Pan-STARRS1 Medium Deep Survey (PS1-MDS) for rapidly evolving and luminous transients. We identify 10 new transients with a time above half-maximum (t_1/2) of less than 12 days and -16.5 > M > -20 mag. This increases the number of known events in this region of SN phase space by roughly a factor of three. The median redshift of the PS1-MDS sample is z = 0.275 and they all exploded in star-forming galaxies. In general, the transients possess faster rise than decline timescale and blue colors at maximum light (g_P1-rP1 ≲ -0.2). Best-fit blackbodies reveal photospheric temperatures/radii that expand/cool with time and explosion spectra taken near maximum light are dominated by a blue continuum, consistent with a hot, optically thick, ejecta. We find it difficult to reconcile the short timescale, high peak luminosity (L > 10⁴³erg s^-1), and lack of UV line blanketing observed in many of these transients with an explosion powered mainly by the radioactive decay of ⁵⁶Ni. Rather, we find that many are consistent with either (1) cooling envelope emission from the explosion of a star with a low-mass extended envelope that ejected very little (<0.03 M) radioactive material, or (2) a shock breakout within a dense, optically thick, wind surrounding the progenitor star. After calculating the detection efficiency for objects with rapid timescales in the PS1-MDS we find a volumetric rate of 4800-8000 events yr^-1Gpc^-3(4%-7% of the core-collapse SN rate at z = 0.2).

Local Conventions in Game Play in an Evolving Dual Social Network Framework

People usually perform economic interactions within the social setting of a small group, while they obtain relevant information from a broader source. We capture this feature with a dynamic interaction model based on two separate social networks. Individuals play a coordination game in an interaction network, while updating their strategies using information from a separate influence network through which information is disseminated. In each time period, the interaction and influence networks co-evolve, and the individuals’ strategies are updated through a modified naive learning process. We show that both network structures and players’ strategies always reach a steady state, in which players form fully connected groups and converge to local conventions. We also analyze the influence exerted by a minority group of strongly opinionated players on these outcomes.

Land wars in India: Contestations, social forces and evolving neoliberal urban transformation

Land wars in India: Contestations, social forces and evolving neoliberal urban transformation
The recent incidents of ‘land wars’ in India have highlighted the contradictions and challenges of the neoliberal urban transformation through a range of issues across governance, equity and empowerment in the development agenda. Simply put, a strong top down approach and corporate-political nexus have determined the modality of land acquisition, compensation and ultimately the nature of its consumption leaving out majority urban poor from its benefits. The paper focuses on the concept of neoliberalism as a modality of urban governance and emergence of the grassroots activism as a countermagnate to neoliberalist hegemony by examining the inequity and marginalization that embody these ‘land wars’ in India and the forms of resistance from the grassroots - their capacity, relationship and modus operandi. Emerging lessons suggest the potential for advancing governance from the bottoms up leading to more equitable distribution of resources. It is however argued that there is a need for a stronger conception of the ‘grassroots’ in both epistemological and empirical context. In particular, the preconditions for the ‘grassroots organisations’ to foster and play a more effective role requires a more inclusive notion of ‘institutionality and plurality’ within the current political economic context. The empirical focus of the paper is ‘land wars’ observed in Kolkata, West Bengal, however references to other examples across the country have also been made.

Evolving nature of the AP2 alpha-appendage hub during clathrin-coated vesicle endocytosis

Clathrin-mediated endocytosis involves the assembly of a network of proteins that select cargo, modify membrane shape and drive invagination, vesicle scission and uncoating. This network is initially assembled around adaptor protein (AP) appendage domains, which are protein interaction hubs. Using crystallography, we show that FxDxF and WVxF peptide motifs from synaptojanin bind to distinct subdomains on alpha-appendages, called 'top' and 'side' sites. Appendages use both these sites to interact with their binding partners in vitro and in vivo. Occupation of both sites simultaneously results in high-affinity reversible interactions with lone appendages (e.g. eps15 and epsin1). Proteins with multiple copies of only one type of motif bind multiple appendages and so will aid adaptor clustering. These clustered alpha(appendage)-hubs have altered properties where they can sample many different binding partners, which in turn can interact with each other and indirectly with clathrin. In the final coated vesicle, most appendage binding partners are absent and thus the functional status of the appendage domain as an interaction hub is temporal and transitory giving directionality to vesicle assembly.

Evolving techniques for monitoring geotechnical risk on the Antrim Coast Road.

The interaction between problematic geology and environmental variables along the Antrim Coast Road results in frequent instances of geotechnical instability. During such instances of instability, mudslide debris encroaches on the carriageway posing a hazard to motorists, causing lengthily tailbacks. This paper examines some of the geotechnical and spatial analysis techniques currently being implemented to monitor slope stability on this key transport route.

Evolving techniques for characterising and monitoring the stability of infrastructure slopes

Landslides and debris flows, commonly triggered by rainfall, pose a geotechnical risk causing disruption to transport routes and incur significant financial expenditure. With infrastructure maintenance budgets becoming ever more constrained, this paper provides an overview of some of the developing methods being implemented by Queen’s University, Belfast in collaboration with the Department for Regional Development to monitor the stability of two distinctly different infrastructure slopes in Northern Ireland. In addition to the traditional, intrusive ground investigative and laboratory testing methods, aerial LiDAR, terrestrial LiDAR, geophysical techniques and differential Global Positioning Systems have been used to monitor slope stability. Finally, a comparison between terrestrial LiDAR, pore water pressure and soil moisture deficit (SMD) is presented to outline the processes for a more informed management regime and to highlight the season relationship between landslide activity and the aforementioned parameters.

Averaged Extended Tree Augmented Naive Classifier

This work presents a new general purpose classifier named Averaged Extended Tree Augmented Naive Bayes (AETAN), which is based on combining the advantageous characteristics of Extended Tree Augmented Naive Bayes (ETAN) and Averaged One-Dependence Estimator (AODE) classifiers. We describe the main properties of the approach and algorithms for learning it, along with an analysis of its computational time complexity. Empirical results with numerous data sets indicate that the new approach is superior to ETAN and AODE in terms of both zero-one classification accuracy and log loss. It also compares favourably against weighted AODE and hidden Naive Bayes. The learning phase of the new approach is slower than that of its competitors, while the time complexity for the testing phase is similar. Such characteristics suggest that the new classifier is ideal in scenarios where online learning is not required.

Learning Extended Tree Augmented Naive Structures

This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier where the structure learning step is performed without requiring features to be connected to the class. Based on a modification of Edmonds' algorithm, our structure learning procedure explores a superset of the structures that are considered by TAN, yet achieves global optimality of the learning score function in a very efficient way (quadratic in the number of features, the same complexity as learning TANs). We enhance our procedure with a new score function that only takes into account arcs that are relevant to predict the class, as well as an optimization over the equivalent sample size during learning. These ideas may be useful for structure learning of Bayesian networks in general. A range of experiments shows that we obtain models with better prediction accuracy than naive Bayes and TAN, and comparable to the accuracy of the state-of-the-art classifier averaged one-dependence estimator (AODE). We release our implementation of ETAN so that it can be easily installed and run within Weka.

Learning Bounded Tree-Width Bayesian Networks via Sampling

Learning Bayesian networks with bounded tree-width has attracted much attention recently, because low tree-width allows exact inference to be performed efficiently. Some existing methods [12, 14] tackle the problem by using k-trees to learn the optimal Bayesian network with tree-width up to k. In this paper, we propose a sampling method to efficiently find representative k-trees by introducing an Informative score function to characterize the quality of a k-tree. The proposed algorithm can efficiently learn a Bayesian network with tree-width at most k. Experiment results indicate that our approach is comparable with exact methods, but is much more computationally efficient.

Learning Bayesian Networks with Bounded Tree-Width via Guided Search

Bounding the tree-width of a Bayesian network can reduce the chance of overfitting, and allows exact inference to be performed efficiently. Several existing algorithms tackle the problem of learning bounded tree-width Bayesian networks by learning from k-trees as super-structures, but they do not scale to large domains and/or large tree-width. We propose a guided search algorithm to find k-trees with maximum Informative scores, which is a measure of quality for the k-tree in yielding good Bayesian networks. The algorithm achieves close to optimal performance compared to exact solutions in small domains, and can discover better networks than existing approximate methods can in large domains. It also provides an optimal elimination order of variables that guarantees small complexity for later runs of exact inference. Comparisons with well-known approaches in terms of learning and inference accuracy illustrate its capabilities.

Evaluation of the in vitro biological activities of extracts from carob tree and mediterranean oaks

Dissertação mest., Engenharia Biológica, Universidade do Algarve, 2009

Chemical and microbial changes during the natural fermentation of strawberry tree (Arbutus unedo L.) fruits

Aguardente de medronho is the name given in Portugal to a spirit made from the fermented fruit of Arbutus unedo (strawberry tree), a plant grown in the Mediterranean region. In order to gain a better understanding of the fermentation process, as it is performed in the farms, a natural fermentation with wild microbiota was carried out during 36 days, and some physicochemical and microbiological parameters were studied. The microbial parameters analyzed were total viable, lactic and acetic acids bacteria, and yeast counts. The physicochemical parameters monitored were sugars, minerals, ethanol, organic acids and pH. Yeasts were the main responsible for the fermentation of the fruits, as the lactic and acetic acids bacteria are absent. As the fermentation progressed, the sugars increased during the first 2 days and gradually decreased along the fermentation period. Maintaining the good quality of the product could contribute to the preservation and valorization of traditional resources that are of great importance to prevent their disappearance.